Wind-driven rain assessment for multiple building facade orientations using bias-correction of reanalysis precipitation data across various climates in Indonesia

• Bias-corrected ERA5 reanalysis is used to assess long-term wind-driven rain (WDR). • Local climate influences WDR variability across multiple facade orientations. • The direction associated with maximum WDR informs the optimization of facade protection measures. • WDR categorization supports orientation-based strategies for facade moisture mitigation. Wind-driven rain (WDR) is a significant contributor to building facade degradation, including surface weathering, corrosion, and various other forms of deterioration. The lack of long-term hourly rainfall observations poses a major challenge for WDR assessment. ERA5 provides a potential alternative source of hourly precipitation data, although it contains systematic biases. This study proposes a bias-correction framework applied to ERA5 precipitation at the daily scale, which is subsequently redistributed to the hourly scale to enable WDR calculations across multiple facade orientations. Based on an analysis of 106 sites over the period from 2011 to 2020, the bias correction reduces the frequency of light drizzle events (0–0.1 mm) from 41.5% to 25.0%, increases the proportion of no-rain conditions from 21.8% to 50.9%, and redistributes hourly rainfall occurrences toward higher-intensity classes (e.g., 5–10 mm events increase from 0.49% to 0.82%, and >20 mm events from 0.005% to 0.06%). Using the corrected dataset, WDR exposure was assessed across eight facade orientations spanning diverse climate zones in Indonesia, revealing that the orientations associated with maximum exposure vary according to local climatic characteristics. Annual WDR exposure patterns further indicate that west-facing facades commonly experience moderate to very heavy exposure levels. As a result, the proposed framework provides a pragmatic, first-order approximation of long-term WDR exposure based on daily bias-corrected ERA5 hourly precipitation data, supporting semi-empirical WDR calculations and offering practical guidance for identifying facade orientations with higher exposure to inform adaptive design and mitigation strategies across different climate zones.